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CPS1111 Jitendra Kumar et al.

                               Statistical impact of merger and acquisition in a
                               banking industry: A new generalized time series
                                                    model
                                         Jitendra Kumar, Varun Agiwal
                       Department of Statistics, Central University of Rajasthan, Bandersindri, Ajmer, India

                  Abstract
                  Present paper proposes a new autoregressive time series model to study the
                  behaviour of merger and acquire concept which is equally important as other
                  available theories like structural break, de-trending etc. The main motivation
                  behind newly proposed merged autoregressive (M-AR) model is to study the
                  impact of merger in the parameters as well as  in acquired series. First, we
                  recommend  the  estimation  setup  using  popular  classical  least  square
                  estimation and posterior distribution under Bayesian method with different
                  loss functions. Then, find Bayes factor, full Bayesian significance and credible
                  interval test to know the significance of the merger series. An empirical study
                  on merger in banking system is illustrated for more information about the
                  proposed model/ methodology.


                  Keywords
                  Autoregressive  model;  Break  point;  Merger  &  acquire  series;  Bayesian
                  inference

                  1.  Introduction
                      Time series models are preferred to analyze and establish the functional
                  relationship considering it’s own dependence (Box and Jenkins (1970)) as well
                  as some other covariate(s)/ explanatory series which alike parallel influence
                  the series. However, these covariates may not survive for long run because of
                  merger  with  dependent  series.  Such  type  of  functional  relationship  is  not
                  explored by researchers yet but there are so many linear or non-linear models
                  proposed in time series to analysis in a distinctly circumstances see Chan and
                  Tong (1986), Haggan and Ozaki (1981), Chon and Cohen (1997). On the basis
                  of  efficiency  and  accuracy,  preferred  time  dependent  model  is  chosen  of
                  further analysis and doing forecasting. In daily real-life situations, we have a
                  time series which is recorded as a continuous process for every business and
                  organization. In present competitive market, all financial institutions feed upon
                  the growth of their business by utilizing the available information and follow
                  some basic business principles. But rate of consolidations has been increasing
                  tremendously to achieve the goal of higher profitability and widen business
                  horizon.  For  this,  higher  capability  institutions  have  a  significant  impact
                  directly to weaker institutions. With the change on market strategies, some


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